1. Field of the Invention
This invention relates to DNA microarray technology, and more specifically to methods and kits for identifying autism and autism spectrum disorders in humans.
2. Description of the Prior Art
Several publications are referenced in this application in parentheses in order to more fully describe the state of the art to which this invention pertains. Full citations for these references are found at the end of the specification. The disclosure of each of these publications is incorporated by reference herein in their entirety.
The autism spectrum encompasses a set of complex multigenic developmental disorders that severely impact the development of language, non-verbal communication, and social skills, and are associated with odd, stereotyped, repetitive behavior and restricted interests. To date, diagnosis of these neurologically based disorders relies predominantly upon behavioral observations often prompted by delayed speech or aberrant behavior, and there are no known genes that can serve as definitive biomarkers for the disorders.
Autism and related autism spectrum disorders (including Asperger's Syndrome and pervasive developmental disorder-not otherwise specified (PDD-NOS)) are considered to be among the most devastating psychiatric illnesses affecting children. The three core symptoms of autism spectrum disorders (ASD) are: 1) deficits in social interactions and understanding, 2) aberrant communication and/or language development, and 3) restricted, repetitive, and stereotyped behaviors [1]. To date, there are no definitive molecular or genetic markers that allow unequivocal diagnosis of ASD, with the exceptions of tuberous sclerosis, Rett's Syndrome, and Fragile X Syndrome [2-12]. Together, these genetically defined mutations are present in only a minority of individuals (<10%) within the broad autism spectrum. The majority of diagnoses are dependent on behavioral characteristics, according to DSM-IV guidelines, using questionnaires such as the Autism Diagnostic Interview-Revised (ADI-R) [13] or the Autism Diagnostic Observation Schedule (ADOS) [14], which are structured to evaluate children who are approximately 2 or older in mental age. Although the guidelines are relatively clear, the individual rater's (eg., parents, teachers, clinicians, therapists) perception of the evaluated behavior leaves much room for ambiguity. Moreover, with the more mildly affected individuals (eg., with Asperger's Syndrome), diagnosis is often not made until well after the child starts school and, even then, the child is often diagnosed with other more common disorders (such as attention deficit disorder or learning disability) before Asperger's Syndrome is considered, which delays appropriate intervention and effective educational programming. Thus, there is a great need to identify biomarkers that can be used consistently in a clinical setting to diagnose ASD. Furthermore, it is important to identify biological processes that are associated with specific ASD phenotypes in order to design effective drug therapies targeted to specific individuals.
Although genetic linkage analyses have identified numerous candidate genes for autism [15], there is little consistent data that would support the use of any (or a combination) of these as biomarkers for ASD. Furthermore, each candidate gene alone lends little insight into the pathophysiology of these disorders, which are believed to arise from dysregulation of multiple genes. Recently, attention has turned to transcriptional profiling approaches [16-19], which involve simultaneous, large-scale expression analysis of thousands of genes on a cDNA (or oligonucleotide) microarray slide, to unravel complex psychiatric disorders. The advantage of transcriptional profiling using microarrays is the ability to study multiple genes in the context of functional gene networks within a living cell, as opposed to forward genetic approaches. So far, application of microarrays to the study of autism has been described in just one study on post-mortem brain tissue from autistic subjects and matched tissue controls [20]. Thirty genes were identified as being differentially expressed in autistic brain samples relative to matched tissue controls on a combination of 2 separate array platforms containing 588 or 9374 cDNA probes, indicating that autism is associated with multiple disturbances in gene expression. Of this list, only a few genes related specifically to neurological functions and, of these, the glutamate receptor system was targeted for further study. In a similar vein, a recent bioinformatics analysis of autism positional candidate genes using biological databases and computational gene network prediction software demonstrates that the often disparate results from genetic studies implicating a multitude of different genes can be coalesced into interconnected but distinct pathways centered on a specific gene or genes (e.g., FOS and TP53), or on a particular biological theme, e.g., apoptosis [15]. Both of these studies suggest the involvement of multiple genes not previously associated with autism and illustrate the power of using a global approach to study this complex disorder.
The experimental strategy used in the study reported here was designed to tease out differences in gene expression among genetically identical individuals with ASD which might relate to observed differences in the degree of expression of autistic symptoms. Inasmuch as natural variations in gene expression are especially low for monozygotic twins [21, 22], such a strategy has been shown to be useful in identifying candidate genes for bipolar disorder [23] and osteoporosis [24]. Moreover, lymphoblastoid cell lines (LCL) derived from blood cells of autistic individuals were used in this study to explore the possibility that biomarkers for autism could be expressed in easily accessible peripheral cells. Indeed, it has been reported previously that LCL from individuals with bipolar disorder displayed altered gene expression in both postmortem brain tissue and lymphoblasts, although one of the genes, LIM, was altered in the opposite direction in LCL [25]. Follow-up genetic association analyses of this gene demonstrated association of a single nucleotide polymorphism with bipolar disorder [26], indicating the usefulness of LCL and DNA microarray analyses in identifying potential biomarkers of a complex neurological disease.
While studies of gene expression in brain tissue may lead to a better understanding of the mechanistic basis for ASD, it is not an appropriate target for diagnostic assays. Ideally, diagnostic assays should use easily obtained patient samples such as blood, although there is no evidence that gene expression or other markers exist in the peripheral blood of ASD patients. However, one may hypothesize that ASD might arise, in part, through dysregulation of expression of specific neuronal genes and that expression differences between affected and unaffected individuals might be present in tissues other than brain. As a test of this hypothesis, we chose to use DNA microarray analysis to examine gene expression in LCL derived from peripheral blood lymphocytes.